Program > Browse abstracts by author > Marino Filippo

REXdb is a comprehensive database of conserved protein domain sequences extracted from all TE types occurring in plants [1]. It serves as a basis for the automatic classification of TEs identified with the RepeatExplorer pipeline, but can also be used independently with the DANTE (Domain Based Annotation of Transposable Elements) tool (both available at http://repeatexplorer.org/). Recently, we have implemented the database in DANTE-LTR, a new tool for the identification and hierarchical classification of LTR retrotransposons in lineages (see the poster by Petr Novák). Since the current version of REXdb (Viridiplantae_v3.0) mainly covers domains extracted from elements of angiosperm species, the use of the database for gymnosperms and non-seed species is limited due to lower sensitivity and imperfect classification of some elements. Therefore, we set out to perform a comprehensive study of LTR retrotransposons in these species as well. We found that although the sequences of the reverse transcriptase, RNase H and integrase domains were sufficiently conserved to be unambiguously identified, their divergence from the sequences in REXdb often led to incomplete or even incorrect classification. This was even more dramatic for the GAG and protease domains, which showed a very high sequence divergence that in some cases prevented their reliable identification. Phylogenetic analysis revealed that although some lineages of LTR retrotransposons are common to angiosperms, gymnosperms and non-seed plants, the non-seed plants also contain elements constituting lineages that are missing in the current REXdb classification system. These results have prompted us to expand REXdb to 1) include additional sequences of non-angiosperm elements and 2) incorporate new findings in the phylogeny of plant LTR retrotransposons into the associated classification system. To make our data available to the community, we will soon release a new version of REXdb, Viridiplantae_v4.0.

[1] Neumann et al. 2019, Mobile DNA 10, 1. DOI: 10.1186/s13100-018-0144-1